Citations

Abstract Background: Multiple myeloma (MM) has been studied by conventional cytogenetics and fluorescence in situ hybridization using DNA probes (FISH) on interphase nuclei and metaphase cells, but the relative clinical significance of proliferating (metaphase) versus non-proliferating (interphase) cells at diagnosis is poorly understood. We investigated a consecutive series of 154 patients (pts) with newly diagnosed untreated MM, and compared results for metaphase and interphase cells with survival. Methods: Bone marrow within 30 days of diagnosis was analyzed by standard cytogenetics. Leftover cells were stored at −70°C. Interphase and metaphase FISH was done using probes for IGH, FGFR3, CCND1, c-MAF, D13S319, LAMP1, p53 and D17Z1 to detect t(4;14), t(11;14), t(14;16) and chromosome 13 or 17 anomalies, respectively. We analyzed <10 metaphases and 200 unselected interphase nuclei for each FISH probe set for each pt. Survival rates were estimated using Kaplan-Meier and differences in survival curves compared using log-rank test. Results: 61 (39.6%) pts had abnormal metaphases by cytogenetics (43 pts) and/or FISH (46 pts): 12 (19.7%) had t(11;14) by cytogenetics (3 pts) and/or FISH (11 pts), 11 (18.0%) had t(4;14) by FISH but not cytogenetics, and 3 (4.9%) had t(14;16) by FISH but not cytogenetics. Metaphases with 13q- were seen in 30 pts (49.2%). Interphase FISH results were abnormal for 133 (86.3%) pts: mean percent neoplastic nuclei was 26.9 ± 21.6 (3.9 to 99.0). Mean percent plasma cells was 54.7 ± 24.6 (3.0 to 99.0). Each of the 61 pts with abnormal metaphases was also abnormal in interphase nuclei. Median survival for pts with ≥50% (20 pts) abnormal nuclei was 202 days vs. 1351 days for pts with <50% (134 pts) (p<0.001). Median survival for pts with abnormal metaphases (61 pts) was 587 days vs. 1404 days for pts with normal metaphases (93 pts) (p=0.002). Median survival was 381 days for 30 pts with 13q- metaphases compared with 1404 days for 38 pts with normal metaphases and 13q- interphase nuclei (p<0.001). Metaphase and interphase analysis along with other potential risk factors (hemoglobin <10, serum calcium ≥11, serum creatinine ≥2, plasma cell labeling index and percent bone marrow plasma cells) were evaluated by multivariate analysis using a stepwise selection in a Cox proportional hazards model. Only the observation of 13q- in metaphases or ≥50% abnormal interphase nuclei were significant predictors of survival. Conclusions: Analysis of metaphases at diagnosis is important to detect proliferating disease which is a strong indicator of poor prognosis. Metaphase FISH is a necessary adjunct to conventional cytogenetics to detect cryptic t(4;14) and t(14;16), and accurately detect prognostic chromosome anomalies such as 13q-. Observing a 13q- in metaphase cells is a strong predictor of survival compared with observing 13q- in only interphase nuclei. At diagnosis, analysis of interphase nuclei is efficient, identifies an abnormal clone in 86% of pts and defines a subset of patients with ≥50% nuclei that have a poor prognosis. Since analysis of metaphases gives better prognostic information, interphase FISH is not a substitution in the cytogenetic work up of patients with MM.

OBJECTIVE The nature of the volume-outcome relationship in cases with severe traumatic brain injury (TBI) remains unclear, with considerable interhospital variation in patient outcomes. The objective of this study was to understand the state of the volume-outcome relationship at different levels of trauma centers in the United States. METHODS The authors queried the National Trauma Data Bank for the years 2007–2014 for patients with severe TBI. Case volumes for each level of trauma center organized into quintiles (Q1–Q5) served as the primary predictor. Analyzed outcomes included in-hospital mortality, total hospital length of stay (LOS), and intensive care unit (ICU) stay. Multivariable regression models were performed for in-hospital mortality, overall complications, and total hospital and ICU LOSs to adjust for possible confounders. The analysis was stratified by level designation of the trauma center. Statistical significance was established at p < 0.001 to avoid a type I error due to a large sample size. RESULTS A total of 122,445 patients were included. Adjusted analysis did not demonstrate a significant relationship between increasing hospital volume of severe TBI cases and in-hospital mortality, complications, and nonhome hospital discharge disposition among level I–IV trauma centers. However, among level II trauma centers, hospital LOS was longer for the highest volume quintile (adjusted mean difference [MD] for Q5: 2.83 days, 95% CI 1.40–4.26 days, p < 0.001, reference = Q1). For level III and IV trauma centers, both hospital LOS and ICU LOS were longer for the highest volume quintile (adjusted MD for Q5: LOS 4.6 days, 95% CI 2.3–7.0 days, p < 0.001; ICU LOS 3.2 days, 95% CI 1.6–4.8 days, p < 0.001). CONCLUSIONS Higher volumes of severe TBI cases at a lower level of trauma center may be associated with a longer LOS. These results may assist policymakers with target interventions for resource allocation and point to the need for careful prehospital decision-making in patients with severe TBI.

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 369 nominally genome-wide significant loci ( P < 5 × 10 −8 ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 −10 ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r G = −0.32, SE = 0.05, P = 6.5 × 10 −12 ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure. ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS

PURPOSE Primary endocrine therapy for ductal carcinoma in situ (DCIS) as a potential alternative to surgery has been understudied. This trial explored the feasibility of a short-term course of letrozole and sought to determine whether treatment results in measurable radiographic and biologic changes in estrogen receptor (ER)–positive DCIS. PATIENTS AND METHODS A phase II single-arm multicenter cooperative-group trial was conducted in postmenopausal patients diagnosed with ER-positive DCIS without invasion. Patients were treated with letrozole 2.5 mg per day for 6 months before surgery. Breast magnetic resonance imaging (MRI) was obtained at baseline, 3 months, and 6 months. The primary end point was change in 6-month MRI enhancement volume compared with baseline. RESULTS Overall, 79 patients were enrolled and 70 completed 6 months of letrozole. Of these, 67 patients had MRI data available for each timepoint. Baseline MRI volumes ranged from 0.004 to 26.3 cm 3 . Median reductions from baseline MRI volume (1.4 cm 3 ) were 0.6 cm 3 (61.0%) at 3 months ( P < .001) and 0.8 cm 3 (71.7%) at 6 months ( P < .001). Consistent reductions were seen in median baseline ER H-score (228; median reduction, 15.0; P = .005), progesterone receptor H-score (15; median reduction, 85.0; P < .001), and Ki67 score (12%; median reduction, 6.3%; P = .007). Of the 59 patients who underwent surgery per study protocol, persistent DCIS remained in 50 patients (85%), invasive cancer was detected in six patients (10%), and no residual DCIS or invasive cancer was seen in nine patients (15%). CONCLUSIONS In a cohort of postmenopausal women with ER-positive DCIS, preoperative letrozole resulted in significant imaging and biomarker changes. These findings support future trials of extended endocrine therapy as primary nonoperative treatment of some DCIS.

Background and Aims Statins have been proven to be cytotoxic to human cholangiocarcinoma cells by inhibiting cell division and inducing apoptosis. We aimed to determine the effect of statin use on the risk of cancer development and survival in patients with extrahepatic cholangiocarcinoma (ECC), including perihilar cholangiocarcinoma (pCCA) and distal cholangiocarcinoma (dCCA). Approach and Results A total of 394 patients with ECC and hyperlipidemia who received care at Mayo Clinic Rochester between 2005 and 2015 were matched by age, sex, race, ethnicity, and residency to 788 controls with hyperlipidemia. Clinical and outcome data were abstracted. The odds ratios (ORs) for risk and hazard ratios for outcomes were calculated. The mean age and standard deviation (SD) for cases and controls was 65.6 years (13.8). The number of statin users in cases and controls was 73 (19%) and 403 (51%), respectively. Hepatitis C virus infection (OR, 15.84; 95% confidence interval [CI], 4.06‐61.87; P < 0.001) was the most significant risk factor for pCCA followed by inflammatory bowel disease and cirrhosis, whereas other liver disease, including biliary stone disease (OR, 4.06; CI, 2.24‐7.36; P < 0.001), was the only significant risk factor for dCCA. Statin use was associated with significantly reduced risk for all ECC (OR, 0.22; CI, 0.16‐0.29) as well as for the subtypes pCCA (OR, 0.3; CI, 0.21‐0.41) and dCCA (OR, 0.06; CI, 0.03‐0.14), all P < 0.0001. Moderate‐intensity dosage was found to decrease the risk of ECC (OR, 0.48; CI, 0.34‐0.67; P < 0.001). Comparing statin ever users to nonusers, patients with dCCA who used statins had significantly overall better survival (hazard ratio = 0.53; CI, 0.29‐0.97; P = 0.04). Conclusions This case‐control study suggests that statins decrease the risk of ECC and may improve survival in patients with dCCA. Additional validation studies are warranted.

Abstract Objectives Implicit bias is common and is thought to drive discriminatory behaviour. Having previously demonstrated discrimination against specific applicant demographics by academic radiology departments in a simulated resident selection process, the authors sought to better understand the relationship between implicit bias and discrimination, as well as the potential and mechanisms for their mitigation. Methods A total of 51 faculty reviewers at three academic radiology departments, who had participated in a 2017 audit study in which they were shown to treat applicants differently based on race or ethnicity and physical appearance, were invited to complete testing for implicit racial and weight bias using the Implicit Association Test in 2019. Respondents were also surveyed regarding awareness of their own personal racial and weight biases, as well as any prior participation in formal diversity training. Comparisons were made between implicit bias scores and applicant ratings, as well as between diversity training and self‐awareness of bias. Results A total of 31 out of 51 faculty reviewers (61%) completed and submitted results of race and weight Implicit Association Tests. A total of 74% (23/31) reported implicit anti‐obese bias, concordant with discrimination demonstrated in the resident selection simulation, in which obese applicants were rated 0.40 standard deviations (SDs) lower than non‐obese applicants ( P < .001). A total of 71% (22/31) reported implicit anti‐Black bias, discordant with application ratings, which were 0.47 SDs higher for Black than for White applicants ( P < .001). A total of 84% (26/31) of participants reported feeling self‐aware of potential racial bias at the time of application review, significantly higher than the 23% (7/31) reporting self‐awareness of potential anti‐obese bias ( P < .001). Participation in formal diversity training was not associated with implicit anti‐Black or anti‐fat bias, nor with self‐reported awareness of potential racial or weight‐based bias (all P > .2). Conclusions These findings suggest that implicit bias, as measured by the Implicit Association Test, does not inevitably lead to discrimination, and that personal awareness of implicit biases may allow their mitigation.

AbstractPrevious transcriptome‐wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome‐wide association studies (GWAS), but analyses of breast cancer subtype‐specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta‐analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER−). We further compared associations with ER+ and ER− subtypes, using a case‐only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER– breast cancer. We further identified 30 TWAS‐significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast‐cancer gene in three of six regions harboring multiple TWAS‐significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER− breast cancer.

Background/aims: The difference in mean survival time, which quantifies the treatment effect in terms most meaningful to patients and retains its interpretability regardless of the shape of the survival distribution or the proportionality of the treatment effect, is an alternative endpoint that could be used more often as the primary endpoint to design clinical trials. The underuse of this endpoint is due to investigators’ lack of familiarity with the test comparing the mean survival times and the lack of tools to facilitate trial design with this endpoint. The aim of this article is to provide investigators with insights and software to design trials with restricted mean survival time as the primary endpoint. Methods: A closed-form formula for the asymptotic power of the test of restricted mean survival time difference is presented. The effects of design parameters on power were evaluated for the mean survival time test and log-rank test. An R package which calculates the power or the sample size for user-specified parameter values and provides power plots for each design parameter is provided. The R package also calculates the probability that the restricted mean survival time is estimable for user-defined trial designs. Results: Under proportional hazards and late differences in survival, the power of the mean survival time test can approach that of the log-rank test if the restriction time is late. Under early differences, the power of the restricted mean survival time test is higher than that of the log-rank test. Duration of accrual and follow-up have little influence on the power of the restricted mean survival time test. The choice of restriction time, on the other hand, has a large impact on power. Because the power depends on the interplay among the design factors, plotting the relationship between each design parameter and power allows the users to select the designs most appropriate for their trial. When modification is necessary to ensure the difference in restricted mean survival time is estimable, the three available modifications all perform adequately in the scenarios studied. Conclusion: The restricted mean survival time is a survival endpoint that is meaningful to investigators and to patients and at the same time requires less restrictive assumptions. The biggest challenge with this endpoint is selection of the restriction time. We recommend selecting a restriction time that is clinically relevant to the disease and the clinical setting of the trial of interest. The practical considerations and the R package provided in this work are readily available tools that researchers can use to design trials with restricted mean survival time as the primary endpoint.